Predictive Analytics & Emerging Technologies

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According to Porter & Balu (2016) predictive modeling estimates individuals’ potential outcomes by testing models that use data on subjects whose determined outcomes are already known. While predictive models and analytic data accompany traditional business and marketing efforts, in recent years, they have become a major component in public education. Using data and models to better align learner performance and outcomes is now a focal point of many educational entities. In this same context, emerging technology almost necessitates the need for data analysis and predictive models. In that regard, technology continues to change and must be utilized in ways to better serve students and learners based on their individual and collective needs.

It is necessary for me to stay informed on trends such as predictive analysis and emerging technology, not only as a future instructional technologist, but as someone who values continuing the learning experience myself and expanding my knowledge. Working to better understand predictive models/analysis and the expanding technology that accompanies those resources will continue to be an area of focus when considering educational methods and applications.

In the future I would like to learn more about specific emergent technologies and how they are shaping the learning experience for students. The following article provides a short description of emerging technologies as well as specific examples:

https://elearningindustry.com/top-educational-technology-trends-2020-2021

There is a vast amount of information that is inherent with predictive models and in many ways can be difficult to examine the inherent trends of the data based on individual and collective analysis. In that regard, learning how to view and apply the analytical data toward estimating performance or improvement through early-warning systems is just a fraction of the possible applications when aimed towards better educational experiences for both students and instructors. When results are interpreted correctly, predictive modeling offers benefits to those engaged in continuous improvement efforts and those who are looking to allocate resources more efficiently (Porter & Balu, 2016).

 

Porter, K. E., & Balu, R. (2016, November). Predictive Modeling of K-12 Academic Outcomes. Manpower Demonstration Research Corporation (MDRC). https://www.mdrc.org/sites/default/files/Predictive_Modeling_of_K-12_Academic_Outcomes.pdf

Southern Regional Education Board. (2018, February). 10 Issues in Educational Technology. SREB. https://www.sreb.org/sites/main/files/file-attachments/10issues_v8-web_version_accessible.pdf?1521568731

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